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A Implementation of User Exercise Motion Recognition System Using Smart-Phone
Author(s) -
Seung-Hyun Kwon,
Yue-Soon Choi,
Soon-Ja Lim,
Joung Suck-Tae
Publication year - 2016
Publication title -
journal of the korea academia-industrial cooperation society
Language(s) - English
Resource type - Journals
eISSN - 2288-4688
pISSN - 1975-4701
DOI - 10.5762/kais.2016.17.10.396
Subject(s) - kalman filter , computer science , smart phone , motion (physics) , motion sensors , phone , activity recognition , artificial intelligence , computer vision , real time computing , telecommunications , philosophy , linguistics
Recently, as the performance of smart phones has advanced and their distribution has increased, various functions in existing devices are accumulated. In particular, functions in smart devices have matured through improvement of diverse sensors. Various applications with the development of smart phones get fleshed out. As a result, services from applications promoting physical activity in users have gotten attention from the public. However, these services are about diet alone, and because these have no exercise motion recognition capability to detect movement in the correct position, the user has difficulty obtaining the benefits of exercise. In this paper, we develop exercise motion-recognition software that can sense the user's motion using a sensor built into a smart phone. In addition, we implement a system to offer exercise with friends who are connected via web server. The exercise motion recognition utilizes a Kalman filter algorithm to correct the user's motion data, and compared to data that exist in sampling, determines whether the user moves in the correct position by using a DTW algorithm.

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